The use of photo analytics offers significant advantages for food quality assurance, as much of the current practice includes visual inspection. The challenge for visual inspection of fresh food is twofold: first, the inspector must be highly trained to identify the visual feedback, and interpret according to the specific of the food type and possible variety specifics, and second, the inspector needs to be as objective as possible to enable consistent evaluation across different inspectors potentially in different environments. The use of photo analytics can improve upon inspector visual inspection, by performing consistent evaluations from images of food products. However, the image capture may not be consistent due to a number of potential factors, such as (but not limited to) lighting of the food product, camera filters or optical biases, background color influences, air borne particle interference, non-visible light variability, the type of camera used, and so on.